Structural and Computational Insights into the Mechanism of the Superior Pharmacological Activity of Crisugabalin: A Third-Generation Cavα 2 δ1 Ligand

化学 分子动力学 药效团 离解(化学) 三环 普瑞巴林 氢键 配体(生物化学) 立体化学 计算化学 对接(动物) 分子模型 动力学 蛋白质亚单位 疏水效应 结合位点 分子 生物活性 下部结构 加巴喷丁 离解常数 生物物理学 组合化学
作者
Zhaoqiang Chen,Xiaoli Gou,Qingyuan Meng,He Li,Yao Li,Zongjun Shi,Xinxin Li,Ju Wang
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:66 (1): 632-641 被引量:2
标识
DOI:10.1021/acs.jcim.5c02583
摘要

Crisugabalin, a recently approved third-generation GABA analogue with a unique cage-like tricyclic scaffold, shows superior efficacy and safety over pregabalin and mirogabalin for treating neuropathic pain. Through integrated biophysical, structural, and computational approaches, we elucidate the molecular basis of its enhanced pharmacological profile. Dissociation kinetic studies revealed that crisugabalin exhibited the slowest dissociation kinetics from the α 2 δ1 subunit (τ = 32.05, 80.00, 111.11 min for pregabalin, mirogabalin, and crisugabalin) but the fastest dissociation from the α 2 δ2 subunit (τ = 8.70, 16.39, 5.78 min for pregabalin, mirogabalin, and crisugabalin). Cryo-EM structures demonstrated crisugabalin’s superior binding affinity for α 2 δ1 over gabapentin and l -leucine, driven by enhanced hydrogen bonding and hydrophobic contacts, alongside volumetric expansion of the l -leucine binding pocket. Molecular dynamics (MD) simulations identified significantly more persistent hydrogen bonding by crisugabalin (66.3% average occupancy) relative to pregabalin (28.3%). Random Acceleration Molecular Dynamics (RAMD) simulations revealed that ligand dissociation primarily proceeds via Pathway A (along the β2, β3, and β1 segments), and τRAMD calculations correctly ranked the ligand residence times, yielding values of 0.18 ns for pregabalin and 2.88 ns for crisugabalin. Furthermore, the binding free energies for pregabalin, mirogabalin, and crisugabalin were −21.64, −31.30, and −34.99 kcal/mol, calculated by MM/GBSA. The decomposition of the binding free energy components revealed that crisugabalin exhibits a dual-action mechanism characterized by enhanced hydrophobic interactions (−28.46 kcal/mol) and favorable entropic contributions (3.03 kcal/mol). This unique binding behavior stems from its cage-like tricyclic scaffold, an unprecedented substructure in drug molecules. These findings establish the cage-like tricyclic motif as a novel pharmacophore that simultaneously optimizes binding entropy and enthalpy, providing a blueprint for next-generation voltage-gated calcium channel modulators. MD, τRAMD, and MM-GBSA used in this study are powerful computational tools for rational drug design, particularly for optimizing compounds with prolonged target residence times.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zxy完成签到,获得积分10
刚刚
advance完成签到,获得积分10
刚刚
领导范儿的应助被DW采纳,获得10
刚刚
1秒前
八非土博完成签到,获得积分10
2秒前
Jerry发布了新的文献求助10
2秒前
2秒前
Nowaki完成签到,获得积分10
2秒前
李健的小迷弟的应助被erniu采纳,获得10
2秒前
研友_nPkKEL发布了新的文献求助10
3秒前
4秒前
dadadasds发布了新的文献求助10
4秒前
勤劳颜完成签到,获得积分10
4秒前
wsq发布了新的文献求助10
5秒前
McQueen完成签到,获得积分10
5秒前
lu完成签到,获得积分10
6秒前
6秒前
勤劳颜发布了新的文献求助10
6秒前
7秒前
希望天下0贩的0的应助被anlan采纳,获得10
7秒前
科研通AI6.2的应助被八非土博采纳,获得10
7秒前
阿诺发布了新的文献求助10
7秒前
7秒前
星辰大海的应助被liuchengrui采纳,获得10
7秒前
caihong1发布了新的文献求助10
9秒前
万能图书馆的应助被馒头采纳,获得10
10秒前
xxx发布了新的文献求助10
10秒前
ax发布了新的文献求助10
11秒前
遇晨完成签到 ,获得积分10
11秒前
小蘑菇的应助被药大小金鱼采纳,获得10
11秒前
风中的不平完成签到,获得积分10
12秒前
mini完成签到,获得积分10
12秒前
还行完成签到,获得积分10
13秒前
可爱的路灯完成签到,获得积分10
13秒前
科研通AI6.2的应助被孙快乐采纳,获得10
13秒前
13秒前
14秒前
所所的应助被时尚的墨镜采纳,获得10
14秒前
kkk发布了新的文献求助10
14秒前
皮皮最可爱完成签到 ,获得积分10
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea De Guyane 2000
Energie-Contracting 1500
Klimaschutzrecht durch den Energiesektor im Mehrebenensystem – Ein Rechtsvergleich 1000
Stochastic Models in Operations Research,Vol. 2 600
Guidelines for fracture-safe and fatigue-reliable design of steel structures 600
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8026680
求助须知:如何正确求助?哪些是违规求助? 9467753
关于积分的说明 21228365
捐赠科研通 7597375
什么是DOI,文献DOI怎么找? 3387589
关于科研通互助平台的介绍 2520164
邀请新用户注册赠送积分活动 2424004